Abstract:Fractal image compression (FIC) is a very popular technique in image compression applications due to its simplicity and superior performance. However, it has a major drawback, which is the long encoding time. This is due to the requirement of performing huge similarity search for encoding each small portion in the image. Thus, reducing the search time of FIC while keeping the quality of reconstructed images at acceptable level is still an active research topic. Therefore, this paper has focused on studying the… Show more
“…The dynamic search starts with a domain block nearest to a range block so it has to be coded and expands until it finds a suitably matching domain block or until the completed search. The effect of using a spatial dynamic search approach instead of a matching threshold strategy on the search reduction of standard full-search of FIC algorithm studied in Saad, et al [52],When using the matching threshold strategy, the dynamic search approach begins with the closest domain and continues until after an acceptable matching block is found or the full image is covered. Closed sub-image blocks are selected over distant image blocks, according to the proposed approach.…”
A new processing algorithm based on fractal image compression is proposed for image processing efficiency. An image will partition into non-overlapping blocks called range blocks and overlapping blocks called domain blocks, with the domain blocks generally bigger than the range blocks, to achieve a rapid encoding time. This research introduced a new fast full-search algorithm approach that starts the search for the best matching domain in the range block from the closest points in the range blocks and expands the search until an acceptable match is found or the search is completed to save even more encoding time. The proposed fast full-search approach, despite its simplicity, is more efficient than the standard search method. The search reduction, peak signal to noise ratio, compression ratio, and encoding time of the suggested approach are all examined. The proposed method can encode a 512x512 grayscale Lena image in 0.36 seconds, with a total search reduction of 87% according to experimental results.
“…The dynamic search starts with a domain block nearest to a range block so it has to be coded and expands until it finds a suitably matching domain block or until the completed search. The effect of using a spatial dynamic search approach instead of a matching threshold strategy on the search reduction of standard full-search of FIC algorithm studied in Saad, et al [52],When using the matching threshold strategy, the dynamic search approach begins with the closest domain and continues until after an acceptable matching block is found or the full image is covered. Closed sub-image blocks are selected over distant image blocks, according to the proposed approach.…”
A new processing algorithm based on fractal image compression is proposed for image processing efficiency. An image will partition into non-overlapping blocks called range blocks and overlapping blocks called domain blocks, with the domain blocks generally bigger than the range blocks, to achieve a rapid encoding time. This research introduced a new fast full-search algorithm approach that starts the search for the best matching domain in the range block from the closest points in the range blocks and expands the search until an acceptable match is found or the search is completed to save even more encoding time. The proposed fast full-search approach, despite its simplicity, is more efficient than the standard search method. The search reduction, peak signal to noise ratio, compression ratio, and encoding time of the suggested approach are all examined. The proposed method can encode a 512x512 grayscale Lena image in 0.36 seconds, with a total search reduction of 87% according to experimental results.
“…Real-time image processing models require a lot of computer power. Utilizing picture compression is one technique to cut down on the expensive computation [24]. For the detection-based methods, like Figure 1, researchers use a sliding window to detect the people in an image and then use this information to count the number of people 33, 34].…”
The rapid increase in the global population has led to the emergence of large crowds during public events across various domains such as sports, music festivals, religious gatherings, and political campaigns. If these events are not properly organized and controlled, they have the potential to result in disasters. Tragically, stampedes occur every year, causing fatalities, disappearances, and injuries for many individuals. Therefore, crowd identification, monitoring, and control are problems that will be addressed and discussed in this paper in order to lessen casualties and prevent such catastrophes. The objective of this study is to present a thorough review of technologies and methods relevant to crowd management, planning, behaviour analysis, and counting. Furthermore, it aids researchers' future progress by examining recent technology developments in the field of crowd planning and monitoring.
“…To reduce the required number of matching operations, the searched blocks are restricted to that exist only on the area close to the corresponding range block. This generally will not cause a noticeable degradation in the quality of the decoded image as the correlation among the adjacent blocks is generally high, specifically for images captured from natural scenes [5,39,40]. Therefore, in this work, each range block in window is compared with every domain blocks s in the same window.…”
Fractal compression technique is a well-known technique that encodes an image by mapping the image into itself and this requires performing a massive and repetitive search. Thus, the encoding time is too long, which is the main problem of the fractal algorithm. To reduce the encoding time, several hardware implementations have been developed. However, they are generally developed for grayscale images, and using them to encode colour images leads to doubling the encoding time 3x at least. Therefore, in this paper, new high-speed hardware architecture is proposed for encoding RGB images in a short time. Unlike the conventional approach of encoding the colour components similarly and individually as a grayscale image, the proposed method encodes two of the colour components by mapping them directly to the most correlation component with a searchless encoding scheme, while the third component is encoded with a search-based scheme. This results in reducing the encoding time and also in increasing the compression rate. The parallel and deep-pipelining approaches have been utilized to improve the processing time significantly. Furthermore, to reduce the memory access to the half, the image is partitioned in such a way that half of the matching operations utilize the same data fetched for processing the other half of the matching operations. Consequently, the proposed architecture can encode a 1024x1024 RGB image within a minimal time of 12.2 ms, and a compression ratio of 46.5. Accordingly, the proposed architecture is further superior to the state-of-the-art architectures.INDEX TERMS Digital circuits, field programmable gate arrays, fractal colour image compression, parallel architectures, pipeline processing.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.